3D Foot Scans: Learn How The Accuracy of Volumental's AI Elevate The Footwear Retail Experience

The following sections in this article provide a quick and easy overview of AI,  machine learning (ML), computer vision (CV), and how Volumental’s algorithms help predict comfortable footwear.

What is AI?

A basic definition of artificial intelligence is a computer system that mimics how a human brain works; it is trained and evaluated on real-world data (like foot scans), solving basic to challenging problems. 

What is Machine Learning and How Does It Help Match Foot Shape to Shoes? 

Machine learning is an application of AI that trains on existing data to help make predictions or decisions for new data. 

The most powerful feature with ML is how the algorithm improves over time, becoming more accurate while rapidly mining massive lakes of data. For example, the algorithm processes and builds footwear recommendations with each customer scan matched to purchases with similar foot shapes. Impressive, right? But ML is not the only technology used to solve fit; it’s also combined with computer vision.

What is Computer Vision and How Does It Help With Fit Recommendation Accuracy?

In a nutshell, computer vision helps algorithms understand the world visually, in forms like video and images. And in the last few years, this technology has vastly improved, making CV a critical tool for accurate foot scans. 

If you've used a smartphone or digital camera for videos or images recently, then you've seen how computers capture images - almost better than human vision.

Volumental 3D foot scanners use CV to help scrub out the noise. Like when you take a selfie, and it looks distorted, pixelated, or has a low light resolution - that's digital noise. When an abrupt change in the value of pixels happens during a scan our algorithms fix this for the most accurate foot scan.

For example, noise can occur when someone moves during an in-store foot scan or quickly during a mobile scan. Noise is dependent on many environmental factors. But our team of engineers built algorithms to adjust for these factors, and our scanners quickly filter out the noise to deliver a clear foot scan.

Retail Fit Technology - Volumental 3D Foot Scans Use The Power of Algorithms for Accuracy

Artificial Intelligence is a game-changer for retail technology. Retailers can have the power of AI to help with the entire ecosystem of selling footwear - from inventory optimization (only showing items in stock) to delivering a fit experience everywhere your customers shop.

Sure, anyone can claim "accuracy" matching length and width to a standard shoe size chart. That's easy. Other techniques require an enormous amount of time, like scanning the inside of shoes or casts, but both of these techniques don't solve the heart of the matter. When foot shapes are matched to purchase data from other customers with similar foot shapes, sizes, and preferences, this is accuracy at its finest.

Accuracy and data insights are why many brands and retailers trust and use Voluemtnal’s FitTech™ platform. "From a consumer perspective, they find the technology highly engaging and easy to understand,” John Davidson, senior brand manager of Bauer said. “As a brand, we are gaining a much deeper insight into the core consumer."

Below are a few helpful questions for retailers or brands comparing 3D foot scanners and FitTech™ platforms:

1. Does the app solution go beyond measuring standard “feet size to shoe size” guidelines?
   
   
2. Does the platform allow you to create a  personalized experience for each shopper?
   
   
3. How does the mobile scanning solution perform out in the wild? While some mobile solutions can work well in a lab situation, how well do they work in various real-world scenarios, like a tiled kitchen floor with someone wearing black socks or in a teenager’s messy bedroom? 
   
   
4. How often does the scanner provider do software updates? Is the system set up so it is future-proofed to optimize for the latest technologies and data insights? If it’s not at least one software update every two weeks, brace yourself for trouble. 
   
   
5. How can you get the most use out of the data captured to improve the experience itself, as well as the current and future products you sell?